In the processing of sequences of digital images from highway traffic scenes for the purposes of detection, tracking and classification of vehicles, there is often the disturbing effect that the vehicles throw a shadow on the highway in the event of there being direct sunshine, the shadow not being able to be separated in a simple way from the vehicle. As a result, a classification of vehicles according to their geometrical dimensions, in particular according to their width, is often made more difficult, if not impossible.
Previous approaches to solving this problem fall back on vehicle models (G. D. Sullivan, K. D. Baker: Model-based vision: using cues to select hypotheses. SPIE Vol. 654 Automatic Optical Inspection (1986), pp. 272-277), which are brought into coincidence with the image (matching), as a result of which separating the shadow is not necessary. This approach has the disadvantage, however, that it is very computation-intensive and that, given the present state of development of image processing hardware, an implementation of such methods in real time within a useful cost frame does not appear possible.